Method, apparatus, electronic device and storage medium for data processing

ABSTRACT

A method for data processing is provided. The method includes obtaining first retrieving data associated with a first user and a first retrieving result selected by the first user from at least one retrieving result corresponding to the first retrieving data. The first retrieving data is labelled with an intention tag indicating a retrieving intention of the first user. The method further includes obtaining second retrieving data that is used by a second user to conduct retrieving and selecting the first retrieving result within a predetermined time period. The method further includes assigning the intention tag to the second retrieving data.

CROSS REFERENCE TO RELATED APPLICATION

This application claims priority to Chinese Patent Application No.202110901941.2 filed on Aug. 6, 2021, the contents of which are herebyincorporated by reference in their entirety for all purposes.

TECHNICAL FIELD

The present disclosure relates to the field of artificial intelligence,particularly relates to an intention recognition technology, andspecifically relates to a method, an apparatus, an electronic device, acomputer readable storage medium and a computer program product for dataprocessing.

BACKGROUND

When a user conducts search or retrieving on the input retrieving datathrough a search engine, the intention recognition for these retrievingdata may be used to analyze the user's retrieving requirements, such aslooking for movies, novels, or encyclopedia knowledge and so on.Different requirements would lead to differences in terms of theunderlying retrieving strategy. The intention recognition that is notcorrect may cause a failure for retrieving the contents that meet theuser's requirements. Therefore, the accurate intention recognition isparticularly important in practical applications.

Methods described in this section are not necessarily those previouslyenvisaged or adopted. Unless otherwise specified, it should not beassumed that any method described in this section is considered theprior art only because it is included in this section. Similarly, unlessotherwise specified, the issues raised in this section should not beconsidered to have been universally acknowledged in any prior art.

SUMMARY

The present disclosure provides a method, an apparatus, an electronicdevice, a computer readable storage medium and a computer programproduct for data processing.

According to an aspect of the present disclosure, a method for dataprocessing is provided, including obtaining first retrieving dataassociated with a first user and a first retrieving result selected bythe first user from at least one retrieving result corresponding to thefirst retrieving data, wherein the first retrieving data is labelledwith an intention tag indicating a retrieving intention of the firstuser; obtaining second retrieving data that is used by a second user toconduct retrieving and selecting the first retrieving result within apredetermined time period; and assigning the intention tag to the secondretrieving data.

According to another aspect of the present disclosure, an electronicdevice is provided, including at least one processor; and a memory incommunication connection with the at least one processor, wherein thememory stores instructions executable by the at least one processor, andthe instructions, when executed by the at least one processor, cause theat least one processor to perform the method as described above.

According to another aspect of the present disclosure, a non-transitorycomputer readable storage medium storing computer instructions isprovided, wherein the computer instructions are configured to cause acomputer to perform the method as described above.

It should be understood that the content described in this part is notintended to identify key or important features of the embodiments of thepresent disclosure, nor is it used to limit the scope of the presentdisclosure. Other features of the present disclosure will be easilyunderstood by the following description.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings exemplarily illustrate embodiments and formpart of the description, which, together with the textual description ofthe description, is used to explain example implementations of theembodiments. The illustrated embodiments are for illustrative purposesonly and do not limit the scope of the claims. In all the drawings, thesame reference numerals refer to similar but not necessarily identicalelements.

FIG. 1 shows a schematic diagram of an example system in which variousmethods and apparatuses described herein may be implemented according toan embodiment of the present disclosure.

FIG. 2 shows a flow diagram of a method for data processing according toan embodiment of the present disclosure.

FIG. 3A and FIG. 3B show schematic diagrams used to illustrate a methodfor data processing according to an embodiment of the presentdisclosure.

FIG. 4 shows a block diagram of a data processing apparatus according toan embodiment of the present disclosure.

FIG. 5 shows a block diagram of a data processing apparatus according toanother embodiment of the present disclosure.

FIG. 6 shows a structural block diagram of an electronic device capableof being applied to an embodiment of the present disclosure.

DETAILED DESCRIPTION

The example embodiments of the present disclosure are described below incombination with the accompanying drawings, including various details ofthe embodiments of the present disclosure to facilitate understanding,which should be considered as only an example. Therefore, those ofordinary skill in the art should recognize that various changes andmodifications may be made to the embodiments described herein withoutdeparting from the scope of the present disclosure. Similarly, forclarity and conciseness, the description of well-known functions andstructures is omitted from the following description.

In the present disclosure, unless otherwise specified, the terms“first”, “second” and the like are used to describe various elements andare not intended to limit the positional relationship, temporalrelationship or importance relationship of these elements. These termsare only used to distinguish one element from another element. In someexamples, a first element and a second element may point to the sameinstance of the element, and in some cases, based on the contextdescription, they can also refer to different instances.

The terms used in the description of the various examples in the presentdisclosure are only for the purpose of describing specific examples andare not intended to be limiting. Unless the context clearly indicatesotherwise, if the number of elements is not specifically limited, theelement may be one or more. In addition, the term “and/or” as used inthe present disclosure covers any and all possible combinations of thelisted items.

In the related art, in the case that the retrieving data involves with ashort text, it usually may not possess a sufficient context and may lacka rigid grammatical structure, which might lead to difficulties in theintention recognition for the retrieving data. In addition, theintention recognition usually needs to be fine-grained, so that the userrequirements can be classified in details. The properties of the shorttext would make it difficult to perform such fine-grained intentionrecognition. In particular, for certain highly professional retrievingdata, such as the medicine-related retrieving data, it is not onlynecessary to analyze that the retrieving data is about a medicationquery, but also to distinguish whether the user specifically needs themedication guidelines, the contraindications, the drug price comparison,etc. In this case, labelling these fine-grained intentions oftenrequires participation of the highly professional personnel, such asmedical experts. However, this may lead to a large consumption of timeand cost. Therefore, for these highly professional retrieving data,there is often a lack of corresponding labelled data or only a smallamount of labelled data is involved, which is not beneficial for thesubsequent training of a model for short text classification.

Aiming at the above problems, a method for data processing is providedaccording to an aspect of the present disclosure. The embodiments of thepresent disclosure will be described in detail below in combination withthe accompanying drawings.

FIG. 1 shows a schematic diagram of an example system 100 in whichvarious methods and apparatuses described herein may be implementedaccording to an embodiment of the present disclosure. Referring to FIG.1, the system 100 includes one or more client devices 101, 102, 103,104, 105 and 106, a server 120 and one or more communication networks110 coupling the one or more client devices to the server 120. Theclient devices 101, 102, 103, 104, 105 and 106 may be configured toexecute one or more applications.

In the embodiment of the present disclosure, the server 120 may run oneor more services or software applications enabling the method for dataprocessing according to the embodiment of the present disclosure.

In certain embodiments, the server 120 may further provide otherservices or software applications that may include non-virtualenvironments and virtual environments. In certain embodiments, theseservices may be provided as web-based services or cloud services, suchas being provided to users of the client devices 101, 102, 103, 104, 105and/or 106 under a software as a service (SaaS) model.

In a configuration as shown in FIG. 1, the server 120 may include one ormore components implementing functions executed by the server 120. Thesecomponents may include a software component, a hardware component ortheir combinations that may be executed by one or more processors. Theusers operating the client devices 101, 102, 103, 104, 105 and/or 106may sequentially utilize one or more client applications to interactwith the server 120 so as to utilize the services provided by thesecomponents. It should be understood that various different systemconfigurations are possible, which may be different from those of thesystem 100. Therefore, FIG. 1 is an example of a system for implementingthe various methods described herein, and is not intended to belimiting.

A data source for the method for data processing according to theembodiment of the present disclosure may be provided by the users usingthe client devices 101, 102, 103, 104, 105 and/or 106. The clientdevices may provide interfaces enabling the users of the client devicesto be capable of interacting with the client devices. The client devicesmay further output information to the users via the interfaces. AlthoughFIG. 1 only depicts six client devices, those skilled in the art canunderstand that the present disclosure may support any number of clientdevices.

The client devices 101, 102, 103, 104, 105 and/or 106 may includevarious types of computer devices, such as a portable handheld device, ageneral-purpose computer (such as a personal computer and a laptopcomputer), a workstation computer, a wearable device, a gaming system, athin client, various message transceiving devices, a sensor or othersensing devices, etc. These computer devices may run various types andversions of software applications and operating systems, such asMicrosoft Windows, Apple iOS, UNIX-like operating systems, and Linux orLinux-like operating systems (such as Google Chrome OS); or includevarious mobile operating systems, such as Microsoft Windows Mobile OS,iOS, Windows Phone and Android. The portable handheld device may includea cell phone, a smart phone, a tablet computer, a personal digitalassistant (PDA) and the like. The wearable device may include ahead-mounted display and other devices. The gaming system may includevarious handheld gaming devices, gaming devices supporting the Internetand the like. The client devices can execute various differentapplications, such as various Internet-related applications,communication applications (such as e-mail applications), and shortmessage service (SMS) applications, and may use various communicationprotocols.

The network 110 may be any type of network well known to those skilledin the art, which may use any one of various available protocols(including but not limited to TCP/IP, SNA, IPX, etc.) to support datacommunication. Only as examples, one or more networks 110 may be a localarea network (LAN), an Ethernet-based network, a token ring, a wide areanetwork (WAN), the Internet, a virtual network, a virtual privatenetwork (VPN), an intranet, an external network, a public switchedtelephone network (PSTN), an infrared network, a wireless network (e.g.,Bluetooth, WiFi), and/or any combination of these and/or other networks.

The server 120 may include one or more general-purpose computers,dedicated server computers (e.g., PC (personal computer) servers, UNIXservers, and midrange servers), blade servers, mainframe computers,server clusters, or any other suitable arrangement and/or combination.The server 120 may include one or more virtual machines running virtualoperating systems, or other computing frameworks involvingvirtualization (e.g., one or more flexible pools of logical storagedevices that may be virtualized to maintain virtual storage devices ofthe server). In various embodiments, the server 120 may run one or moreservices or software applications providing the functions describedbelow.

A computing unit in the server 120 may run one or more operating systemsincluding any above operating system and any commercially availableserver operating system. The server 120 may further run any one ofvarious additional server applications and/or intermediate layerapplications, including an HTTP server, an FTP server, a CGI server, aJAVA server, a database server and the like.

In some implementations, the server 120 may include one or moreapplications to analyze and combine the data feed and/or the eventupdating received from the users of the client devices 101, 102, 103,104, 105 and 106. The server 120 may further include one or moreapplications to display the data feed and/or the real-time events viaone or more display devices of the client devices 101, 102, 103, 104,105 and 106.

In some implementations, the server 120 may be a server of a distributedsystem, or a server combined with a block chain. The server 120 may alsobe a cloud server, or a smart cloud computing server or smart cloud hostwith the artificial intelligence technology. The cloud server is a hostproduct in a cloud computing service system to solve the problems fordifficult management and weak business expansion in a traditionalphysical host and Virtual Private Server (VPS) services.

The system 100 may further include one or more databases 130. In certainembodiments, these databases may be used to store data and otherinformation. For example, one or more of the databases 130 may be usedto store, for example, information of video files and video files. Thedatabase 130 may reside at various positions. For example, the databaseused by the server 120 may be local to the server 120 or may be awayfrom the server 120 and may communicate with the server 120 via andbased on a network or specific connection. The database 130 may be ofdifferent types. In certain embodiments, the database used by the server120 may be a relational database. One or more of these databases mayrespond to a command to store, update and retrieving data to and fromthe databases.

In certain embodiments, one or more of the databases 130 may further beused by applications to store application data. The databases used bythe applications may be different types of databases, such as a keyvalue storage base, an object storage base or a conventional storagebase supported by a file system.

The system 100 of FIG. 1 may be configured and operated in various modesso as to be capable of applying various methods and apparatusesdescribed according to the present disclosure.

FIG. 2 shows a flow diagram of a method 200 for data processingaccording to an embodiment of the present disclosure. As shown in FIG.2, the flow diagram of the method 200 according to the embodiment of thepresent disclosure includes the following steps:

S202, first retrieving data associated with a first user and a firstretrieving result selected by the first user from at least oneretrieving result corresponding to the first retrieving data areobtained, wherein the first retrieving data is labelled with anintention tag indicating a retrieving intention of the first user;

S204, second retrieving data that is used by a second user to conductretrieving and selecting the first retrieving result within apredetermined time period is obtained; and

S206, the intention tag is assigned to the second retrieving data.

According to the method for data processing of the present disclosure,in consideration of the fact that the users selecting the sameretrieving result are supposed to have the same retrieving intention,assuming that the retrieving intention of the first user for selecting acertain retrieving result to conduct retrieving through the firstretrieving data is known, if the other second user selects the sameretrieving result during his retrieving, it implies that the second usershould have the same retrieving intention as the first user. By trackingthe second retrieving data used by the second user to conductretrieving, it may have the same intention tag as the first retrievingdata. Therefore, a large amount of retrieving data labelled with theretrieving intention can be generated or created, and thus dataenhancement of the training data can be achieved. In addition, theprocess of data enhancement does not rely on a traditional naturallanguage processing mode (such as synonym replacement, noise adding,random word adding and deleting, etc.), and thus the diversity of thedata can be improved.

In step S202, the first retrieving data that have been used by the firstuser and the first retrieving result selected by the first user from thecorresponding at least one retrieving result may be obtained. Forexample, the first retrieving data may come from a certain user A. Theprocess that the user A conducts retrieving on the first retrieving datathrough a search engine (such as the search engine developed by Baiducompany) may be recorded and retained by the search engine. Assumingthat the first retrieving data is a retrieving statement such as “whatmedicine should be taken for headache”, at least one retrieving resultmay be generated after retrieving through the search engine.Accordingly, the retrieving result selected from the at least oneretrieving result by the user A may also be obtained through the searchengine.

Herein, the first retrieving data may be a piece of retrieving data, ormay be a retrieving data set including a plurality of pieces ofretrieving data, and its number is not limited in the presentdisclosure. In the case that the first retrieving data involves with theretrieving data set, the retrieving data included therein may come fromdifferent users, for example, from a user B, or a user C, etc., which isdifferent from the user A. Accordingly, the obtained retrieving resultalso corresponds to the above individual users. These retrieving datamay be associated with each other, or may not have any correlation witheach other. In addition, in the case that the first retrieving datainvolves with the retrieving data set, the data volume of the retrievingdata included therein, however, may be small. This is because forcertain highly professional retrieving data, such as themedicine-related retrieving data as described above, the data volume maybe inherently small since the labelling may lead to a large consumptionof time and cost.

In addition, the first retrieving data may be the retrieving data thathave been labelled with the retrieving intention. That is, the firstretrieving data may have the intention tag, which may be used toindicate the retrieving intention of the first user.

According to some embodiments, the first retrieving data may be a textor an image. In this way, the data enhancement of various data can beachieved by utilizing the text searching and image searching functionsprovided by the search engine, such that the method of the presentdisclosure is not only suitable for the text-type data, but also can beextended to the image data.

In the case that the first retrieving data involves with the text, itmay be in the form of a retrieval statement composed of a completesentence, or may be in the form of retrieving words composed of aplurality of discrete words. For example, the first retrieving data maybe a retrieving statement such as “what medicine should be taken forheadache”, and may also be retrieving words such as “headache medicinetaking”. Accordingly, the intention tag may indicate the retrievingintention about the medication query of the user. As a reference, forthe medicine-related retrieving data as described above, there may bequite a lot fine-grained retrieving intentions involved, for example, adozen of fine-grained retrieving intentions may be involved. In additionto the aforementioned retrieving intention about the medication query ofthe user, other retrieving intentions about e.g. the medicationguidelines, the contraindications, the drug price comparison and so onmay be included.

In the case that the first retrieving data involves with the image, itmay be in the form of the image. That is, this situation may correspondto a function of “search by image” provided by the search engine. Forexample, the first retrieving data may be a picture about a Labradordog. Accordingly, the intention tag carried by the first retrieving datamay indicate a retrieving intention of the user about inquiring the dogtype.

According to some embodiments, the at least one retrieving resultincludes at least one web link obtained by conducting retrieval on thefirst retrieving data. Taking an example that the first retrieving dataof the user A is “what medicine should be taken for headache” asdescribed above, a plurality of retrieving results, i.e., web titlesthat have respective web links, may be displayed on an interface of thesearch engine through the retrieving. Therefore, the web link clicked bythe user A among these displayed retrieving results can be obtained.

A principle utilized in the present disclosure is set forth here.Assuming that the users clicking the same web link have the sameretrieving intention, in the case that a web link clicked by the user Awith the known retrieving intention is obtained, if another user, suchas a user X, clicks the same web link as well during the retrieval, itindicates that this user should have the same retrieving intention asthe user A. In this case, if the retrieving data used by the user X toconduct retrieving is traced back, it may have the same intention tag asthe first retrieving data. Thus, a large amount of retrieving datalabelled with the retrieving intention can be generated or created.

Therefore, with the aid of the web links, the traceability of theretrieving data used by the second user to conduct retrieving isprovided, which in turn provides a basis for the implement of thesubsequent data enhancement.

According to some embodiments, the first retrieving result includes aweb link selected by the first user for the first time or for the lasttime from the at least one web link.

Since the retrieving result is usually displayed in the form of a webtitle on a page of the search engine, where the web title may oftenreflect the actual retrieving intention of the user accurately, theretrieving result selected by the user for the first time or for thelast time may be considered as an optimal retrieving result that bestreflects the retrieving intention of the user. Therefore, the retrievingdata with the accurate intention tag can be obtained.

In step S204, the principle as described above is utilized as follows:assuming that the users clicking the same web link have the sameretrieving intention, if the retrieving data used by another user whoclicks the same web link is traced back, it may have the same intentiontag with the first retrieving data.

Similar to obtaining the first retrieving data and the first retrievingresult of the first user, the corresponding retrieving data, i.e., thesecond retrieving data that is used by the second user to conductretrieving may also be crawled through the search engine.

The predetermined time period may be set according to actual conditions,such as three months. Considering that the web links may have asituation of expiration over time, a length of the predetermined timeperiod may be properly adjusted. For example, the retrieving data, suchas “what are the medicines for relieving headache” that is used by theuser X, who clicks within three months the retrieving result (i.e., theweb link) selected by the user A, may be crawled through the searchengine.

In step S206, since the second retrieving data having the sameretrieving intention as the first retrieving data in step S202 areobtained through step S204, the intention tag of the first retrievingdata may then be assigned to the second retrieving data, so that a largeamount of retrieving data labelled with the retrieving intention can begenerated or created.

According to some embodiments, assigning the intention tag to the secondretrieving data may further include determining whether the second userand the first user are the same; and in response to determining that thesecond user and the first user are not the same, labelling the secondretrieving data with the intention tag.

In this way, the retrieving data used by the second user that isdifferent from the first user can be obtained in the first place, sothat diversified retrieval expressions that are used by these differentusers who have differences in aspects such as a personal background andan educational status etc. are utilized, thereby bringing even more datadiversities to improve the data enhancement effect.

According to some embodiments, the first retrieving data and the secondretrieving data may be combined as training data for training aclassification model. Therefore, a large amount of retrieving datalabelled with the retrieving intention can be generated or created.

Here, the classification model may be, for example, a model for shorttext classification. The present disclosure does not limit the types ofthe neural networks adopted by the model. For example, it may be a deepneural network model.

As described above, according to the method for data processing of thepresent disclosure, in consideration of the fact that the usersselecting the same retrieving result are supposed to have the sameretrieving intention, assuming that the retrieving intention of thefirst user for selecting a certain retrieving result to conductretrieving through the first retrieving data is known, if the othersecond user selects the same retrieving result during his retrieving, itimplies that the second user should have the same retrieving intentionas the first user. By tracking the second retrieving data used by thesecond user to conduct retrieving, it may have the same intention tag asthe first retrieving data. Therefore, a large amount of retrieving datalabelled with the retrieving intention can be generated or created, andthus data enhancement of the training data can be achieved. In addition,the process of data enhancement does not rely on a traditional naturallanguage processing mode (such as synonym replacement, noise adding,random word adding and deleting, etc.), and thus the diversity of thedata can be improved.

FIG. 3A and FIG. 3B show schematic diagrams used to illustrate a methodfor data processing according to an embodiment of the presentdisclosure.

FIG. 3A exemplarily shows an example of retrieving data 310 “whatmedicine should be taken for headache” associated with the user A and aselection of a retrieving result 313 from a plurality of retrievingresults 311 to 314 by the user A. As shown in FIG. 3A, the plurality ofweb links 311 to 314 obtained through retrieval are shown, among whichthe web link 313 is the web link that is clicked by the user for thefirst time. As described above, the retrieving data 310 has beenlabelled with the intention tag for the retrieving intention of the userA. For example, the intention tag may indicate the retrieving intentionof performing the medication query of the user A.

FIG. 3B shows a retrieval history of the user B who clicks the same weblink 313 within three months, which is crawled through the searchengine. As shown in FIG. 3B, retrieving data 320 used by the user B whoclicks the same web link 313 to conduct retrieving is “what are themedicines for relieving headache” as shown. That is, the user B clicksthe web link 313 from the plurality of web links 321, 313, 322 and 323.Therefore, the retrieving data 320 of the user B and the retrieving data310 of the user A may be made to have the same intention tag. Theintention tag may indicate the retrieving intention of performingmedication query of the user B.

In this way, more retrieving data labelled with the retrievingintention, such as the retrieving data 320, can be generated or createdbased on the retrieving data 310 labelled with the retrieving intentionassociated with the user A, so that the data enhancement of the trainingdata is achieved. In addition, the data enhancement process does notrely on a traditional natural language processing mode (such as synonymreplacement, noise adding, random word adding and deleting, etc.), andthus the diversity of the data can be improved.

According to another aspect of the present disclosure, a method fortraining a classification model is further provided, including receivingtraining data obtained through the method as described above; andtraining the classification model by using the training data.

According to another aspect of the present disclosure, an apparatus fordata processing is further provided. FIG. 4 shows a block diagram of anapparatus 400 for data processing according to an embodiment of thepresent disclosure. As shown in FIG. 4, the apparatus 400 may include afirst obtaining module 402 configured to obtain first retrieving dataassociated with a first user and a first retrieving result selected bythe first user from at least one retrieving result corresponding to thefirst retrieving data, wherein the first retrieving data is labelledwith an intention tag indicating a retrieving intention of the firstuser; a second obtaining module 404 configured to obtain secondretrieving data that is used by a second user to conduct retrieving andselecting the first retrieving result within a predetermined timeperiod; and a processing module 406 configured to assign the intentiontag to the second retrieving data.

According to some embodiments, the first retrieving data includes a textor an image.

According to some embodiments, the at least one retrieving resultincludes at least one web link obtained by conducting retrieving on thefirst retrieving data.

According to some embodiments, the first retrieving result includes aweb link selected by the first user for the first time or for the lasttime from the at least one web link.

The operations performed by the above modules 402, 404 and 406correspond to steps S202, S204 and S206 described with reference to FIG.2 and FIGS. 3A and 3B, and thus the details thereof are omitted.

FIG. 5 shows a block diagram of an apparatus 500 for data processingaccording to another embodiment of the present disclosure. Modules 502,504 and 506 as shown in FIG. 5 may correspond to the modules 402, 404and 406 as shown in FIG. 4, respectively. In addition, the apparatus 500may further include a functional module 508, and the module 506 mayfurther include sub-functional modules, as will be specificallydescribed below.

According to some embodiments, the processing module 506 may furtherinclude a determining module 5062 configured to determine whether thesecond user and the first user are the same; and a labelling module 5064configured to in response to determining that the second user and thefirst user are not the same, labelling the second retrieving data withthe intention tag.

According to some embodiments, the apparatus 500 may further include acombining module 508 configured to combine the first retrieving data andthe second retrieving data as training data for training aclassification model.

The operations performed by the modules described in combination withFIG. 5 may correspond to the steps of the method described withreference to FIG. 2 and FIGS. 3A and 3B, and thus the details thereofare omitted.

According to another aspect of the present disclosure, a non-transitorycomputer readable storage medium storing computer instructions isfurther provided, wherein the computer instructions are used to cause acomputer to execute the method as described above.

According to another aspect of the present disclosure, a computerprogram product is further provided, including a computer program,wherein the computer program, when executed by a processor, implementsthe method as described above.

According to another aspect of the present disclosure, an electronicdevice is further provided, including at least one processor; and amemory in communication connection with the at least one processor,wherein the memory stores instructions executable by the at least oneprocessor, and the instructions, when executed by the at least oneprocessor, cause the at least one processor to execute the method asdescribed above.

Referring to FIG. 6, a structural block diagram of an electronic device600 that may be applied to the present disclosure will be described, andit is an example of a hardware device that may be applied to variousaspects of the present disclosure. The electronic device is intended torepresent various forms of digital electronic computer devices, such as,a laptop computer, a desktop computer, a workstation, a personal digitalassistant, a server, a blade server, a mainframe computer, and othersuitable computers. The electronic device may further represent variousforms of mobile apparatuses, such as, personal digital processing, acell phone, a smart phone, a wearable device and other similar computingapparatuses. The components shown herein, their connections andrelationships, and their functions are merely used as examples, and arenot intended to limit the implementations of the present disclosuredescribed and/or required herein.

As shown in FIG. 6, the electronic device 600 includes a computing unit601 that may perform various appropriate actions and processingaccording to computer programs stored in a read-only memory (ROM) 602 orcomputer programs loaded from a storage unit 608 into a random accessmemory (RAM) 603. In the RAM 603, various programs and data required foroperations of the electronic device 600 may further be stored. Thecomputing unit 601, the ROM 602 and the RAM 603 are connected to eachother through a bus 604. An input/output (I/O) interface 605 is alsoconnected to the bus 604.

A plurality of components in the electronic device 600 are connected tothe I/O interface 605, including: an input unit 606, an output unit 607,a storage unit 608 and a communication unit 609. The input unit 606 maybe any type of device capable of inputting information to the electronicdevice 600. The input unit 606 may receive input digital or characterinformation and generate key signal input related to user settingsand/or function control of the electronic device, and may include butnot limited to a mouse, a keyboard, a touch screen, a trackpad, atrackball, a joystick, a microphone and/or a remote control. The outputunit 607 may be any type of device capable of presenting information,and may include but not limited to a display, a speaker, a video/audiooutput terminal, a vibrator and/or a printer. The storage unit 608 mayinclude but not limited to a magnetic disk and an optical disk. Thecommunication unit 609 allows the electronic device 600 to exchangeinformation/data with other devices through computer networks such asthe Internet and/or various telecommunication networks, and may includebut not limited to a modem, a network card, an infrared communicationdevice, a wireless communication transceiver and/or a chipset, such as aBluetooth device, a 802.11 device, a WiFi device, a WiMax device, acellular communication device and/or the like.

The computing unit 601 may be various general-purpose and/orspecial-purpose processing components with processing and computingcapabilities. Some examples of the computing unit 601 include but notlimited to a central processing unit (CPU), a graphics processing unit(GPU), various dedicated artificial intelligence (AI) computing chips,various computing units running machine learning model algorithms, adigital signal processor (DSP), and any appropriate processor,controller, microcontroller, etc. The computing unit 601 performsvarious methods and processing described above, such as the method fordata processing. For example, in some embodiments, the method for dataprocessing may be implemented as a computer software program that istangibly included in a machine readable medium, such as the storage unit608. In some embodiments, part or all of the computer programs may beloaded and/or installed onto the electronic device 600 via the ROM 602and/or the communication unit 609. When the computer programs are loadedinto the RAM 603 and executed by the computing unit 601, one or moresteps of the method for data processing described above may beperformed. Alternatively, in other embodiments, the computing unit 601may be configured to perform the method for data processing in any othersuitable manner (for example, by means of firmware).

Various implementations of the systems and technologies described aboveherein may be implemented in a digital electronic circuit system, anintegrated circuit system, a field programmable gate array (FPGA), anapplication specific integrated circuit (ASIC), an application specificstandard part (ASSP), a system on chip (SOC), a load programmable logicdevice (CPLD), computer hardware, firmware, software and/or theircombinations. These various implementations may include: beingimplemented in one or more computer programs, wherein the one or morecomputer programs may be executed and/or interpreted on a programmablesystem including at least one programmable processor, and theprogrammable processor may be a special-purpose or general-purposeprogrammable processor, and may receive data and instructions from astorage system, at least one input apparatus, and at least one outputapparatus, and transmit the data and the instructions to the storagesystem, the at least one input apparatus, and the at least one outputapparatus.

Program codes for implementing the methods of the present disclosure maybe written in any combination of one or more programming languages.These program codes may be provided to processors or controllers of ageneral-purpose computer, a special-purpose computer or otherprogrammable data processing apparatuses, so that when executed by theprocessors or controllers, the program codes enable thefunctions/operations specified in the flow diagrams and/or blockdiagrams to be implemented. The program codes may be executed completelyon a machine, partially on the machine, partially on the machine andpartially on a remote machine as a separate software package, orcompletely on the remote machine or server.

In the context of the present disclosure, a machine readable medium maybe a tangible medium that may contain or store a program for use by orin connection with an instruction execution system, apparatus or device.The machine readable medium may be a machine readable signal medium or amachine readable storage medium. The machine readable medium may includebut not limited to an electronic, magnetic, optical, electromagnetic,infrared, or semiconductor system, apparatus or device, or any suitablecombination of the above contents. More specific examples of the machinereadable storage medium will include electrical connections based on oneor more lines, a portable computer disk, a hard disk, a random accessmemory (RAM), a read only memory (ROM), an erasable programmable readonly memory (EPROM or flash memory), an optical fiber, a portablecompact disk read only memory (CD-ROM), an optical storage device, amagnetic storage device, or any suitable combination of the abovecontents.

In order to provide interactions with users, the systems and techniquesdescribed herein may be implemented on a computer, and the computer has:a display apparatus for displaying information to the users (e.g., a CRT(cathode ray tube) or LCD (liquid crystal display) monitor); and akeyboard and a pointing device (e.g., a mouse or trackball), throughwhich the users may provide input to the computer. Other types ofapparatuses may further be used to provide interactions with users; forexample, feedback provided to the users may be any form of sensoryfeedback (e.g., visual feedback, auditory feedback, or tactilefeedback); an input from the users may be received in any form(including acoustic input, voice input or tactile input).

The systems and techniques described herein may be implemented in acomputing system including background components (e.g., as a dataserver), or a computing system including middleware components (e.g., anapplication server) or a computing system including front-end components(e.g., a user computer with a graphical user interface or a web browserthrough which a user may interact with the implementations of thesystems and technologies described herein), or a computing systemincluding any combination of such background components, middlewarecomponents, or front-end components. The components of the system may beinterconnected by digital data communication (e.g., a communicationnetwork) in any form or medium. Examples of the communication networkinclude: a local area network (LAN), a wide area network (WAN) and theInternet.

A computer system may include a client and a server. The client and theserver are generally far away from each other and usually interactthrough a communication network. The relationship between the client andthe server is generated by computer programs running on thecorresponding computer and having a client-server relationship with eachother.

It should be understood that the various forms of processes shown abovemay be used to reorder, add, or delete steps. For example, the stepsrecorded in the present disclosure may be performed in parallel,sequentially or in different orders, as long as the desired results ofthe technical solution disclosed by the present disclosure can beachieved, which is not limited herein.

In the technical solution of the present disclosure, the acquisition,storage and application of involved personal information of users allcomply with the provisions of relevant laws and regulations, and do notviolate public order and good customs. The intent of the presentdisclosure is that personal information data should be managed andprocessed in a manner that minimizes the risk of inadvertent orunauthorized access to use. The risk is minimized by limiting datacollection and deleting data when it is no longer needed. It should benoted that all information related to personnel in the presentdisclosure is collected with the knowledge and consent of the personnel.

Although the embodiments or examples of the present disclosure have beendescribed with reference to the accompanying drawings, it should beunderstood that the above methods, systems and devices are only exampleembodiments or examples, and the scope of the present invention is notlimited by these embodiments or examples, but only by the authorizedclaims and their equivalent scope. Various elements in the embodimentsor examples may be omitted or replaced by their equivalent elements. Inaddition, the steps may be performed in an order different from thatdescribed in the present disclosure. Further, various elements in theembodiments or examples may be combined in various ways. It is importantthat as technology evolves, many of the elements described herein may bereplaced by equivalent elements that appear after the presentdisclosure.

1. A method for data processing, comprising: obtaining first retrievingdata associated with a first user and a first retrieving result selectedby the first user from at least one retrieving result corresponding tothe first retrieving data, wherein the first retrieving data is labelledwith an intention tag indicating a retrieving intention of the firstuser; obtaining second retrieving data that is used by a second user toconduct retrieving and selecting the first retrieving result within apredetermined time period; and assigning the intention tag to the secondretrieving data.
 2. The method of claim 1, wherein the first retrievingdata comprises a text or an image.
 3. The method of claim 1, wherein theat least one retrieving result includes at least one web link obtainedby conducting retrieving on the first retrieving data.
 4. The method ofclaim 3, wherein the first retrieving result includes a web linkselected by the first user for a first time or for a last time from theat least one web link.
 5. The method of claim 1, wherein assigning theintention tag to the second retrieving data comprises: determiningwhether the second user and the first user are the same; and in responseto determining that the second user and the first user are not the same,labelling the second retrieving data with the intention tag.
 6. Themethod of claim 1, further comprising: combining the first retrievingdata and the second retrieving data as training data for training aclassification model.
 7. An electronic device, comprising: at least oneprocessor; and a memory in communication connection with the at leastone processor, wherein the memory stores instructions executable by theat least one processor, and the instructions, when executed by the atleast one processor, cause the at least one processor to performprocessing comprising: obtaining first retrieving data associated with afirst user and a first retrieving result selected by the first user fromat least one retrieving result corresponding to the first retrievingdata, wherein the first retrieving data is labelled with an intentiontag indicating a retrieving intention of the first user; obtainingsecond retrieving data that is used by a second user to conductretrieving and selecting the first retrieving result within apredetermined time period; and assigning the intention tag to the secondretrieving data.
 8. The electronic device of claim 7, wherein the firstretrieving data comprises a text or an image.
 9. The electronic deviceof claim 7, wherein the at least one retrieving result includes at leastone web link obtained by conducting retrieving on the first retrievingdata.
 10. The electronic device of claim 9, wherein the first retrievingresult includes a web link selected by the first user for a first timeor for a last time from the at least one web link.
 11. The electronicdevice of claim 7, wherein assigning the intention tag to the secondretrieving data comprises: determining whether the second user and thefirst user are the same; and in response to determining that the seconduser and the first user are not the same, labelling the secondretrieving data with the intention tag.
 12. The electronic device ofclaim 7, further comprising: combining the first retrieving data and thesecond retrieving data as training data for training a classificationmodel.
 13. A non-transitory computer readable storage medium storingcomputer instructions, wherein the computer instructions are configuredto cause a computer to perform processing comprising: obtaining firstretrieving data associated with a first user and a first retrievingresult selected by the first user from at least one retrieving resultcorresponding to the first retrieving data, wherein the first retrievingdata is labelled with an intention tag indicating a retrieving intentionof the first user; obtaining second retrieving data that is used by asecond user to conduct retrieving and selecting the first retrievingresult within a predetermined time period; and assigning the intentiontag to the second retrieving data.
 14. The non-transitory computerreadable storage medium of claim 13, wherein the first retrieving datacomprises a text or an image.
 15. The non-transitory computer readablestorage medium of claim 13, wherein the at least one retrieving resultincludes at least one web link obtained by conducting retrieving on thefirst retrieving data.
 16. The non-transitory computer readable storagemedium of claim 15, wherein the first retrieving result includes a weblink selected by the first user for a first time or for a last time fromthe at least one web link.
 17. The non-transitory computer readablestorage medium of claim 13, wherein assigning the intention tag to thesecond retrieving data comprises: determining whether the second userand the first user are the same; and in response to determining that thesecond user and the first user are not the same, labelling the secondretrieving data with the intention tag.
 18. The non-transitory computerreadable storage medium of claim 13, further comprising: combining thefirst retrieving data and the second retrieving data as training datafor training a classification model.